Q 2 LEARNING AND ITS APPLICATION TO CAR MODELLING.

In this paper we describe an application of Q 2 learning, a recently developed approach to machine learning in numerical domains (Šuc et al., 20032004) to the automated modelling of a complex, industrially relevant mechanical system – a four wheel suspension and steering system of a car. In this experiment, first a qualitative model of this dynamic system was induced from data, and then this model was reified into a quantitative model. The induced qualitative models enable explanation of relations among the variables in the system and, when reified into quantitative models, enable accurate numerical prediction. Furthermore, the qualitative guidance of the quantitative modelling process leads to predictions that are significantly more accurate than those obtained by state-of-the-art numerical learning methods. [ABSTRACT FROM AUTHOR]